Effect of Ultrafiltration on Sleep Apnea and Sleep Structure in Patients with End-Stage Renal Disease
Bibliographic record
Abstract
RATIONALE: In end-stage renal disease (ESRD), a condition characterized by fluid overload, both obstructive and central sleep apnea (OSA and CSA) are common. This observation suggests that fluid overload is involved in the pathogenesis of OSA and CSA in this condition. OBJECTIVES: To test the hypothesis that fluid removal by ultrafiltration (UF) will reduce severity of OSA and CSA in patients with ESRD. METHODS: At baseline, on a nondialysis day, patients with ESRD on thrice-weekly hemodialysis underwent overnight polysomnography along with measurement of total body extracellular fluid volume (ECFV), and ECFV of the neck, thorax, and right leg before and after sleep. The following week, on a nondialysis day, subjects with an apnea-hypopnea index (AHI) greater than or equal to 20 had fluid removed by UF, followed by repeat overnight polysomnography with fluid measurements. MEASUREMENTS AND MAIN RESULTS: Fifteen patients (10 men) with an AHI greater than or equal to 20 (10 OSA; 5 CSA) participated. Mean age was 53.5 ± 10.4 years and mean body mass index was 25.3 ± 4.8 kg/m(2). Following removal of 2.17 ± 0.45 L by UF, the AHI decreased by 36% (43.8 ± 20.3 to 28.0 ± 17.7; P < 0.001) without affecting uremia. The reduction in AHI correlated with the reduction in total body ECFV (r = 0.567; P = 0.027) and was associated with reductions in ECFV of the right leg (P = 0.001), overnight change in ECFV of the right leg (P = 0.044), ECFV of the thorax (P = 0.001), and ECFV of the neck (P = 0.003). CONCLUSIONS: These findings indicate that fluid overload contributes to the pathogenesis of OSA and CSA in ESRD, and that fluid removal by UF attenuates sleep apnea without altering uremic status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".